PostgreSQL Training in Iowa

This instructor-led, live training in Iowa equips advanced DevOps professionals and database engineers to implement PostgresAI at enterprise scale. Participants will master database cloning, AI-driven query optimization, and monitoring using hands-on exercises in a live-lab environment.

This 21-hour instructor-led training in Iowa helps data engineers and DBAs integrate AI models into PostgreSQL. Participants learn to deploy optimized architectures, implement vector search, and enforce strict governance, ensuring secure and high-performance enterprise-grade AI solutions.

Master AI integration in Postgres with this instructor-led live training in Iowa. Learn to configure extensions, implement pgvector embeddings, and connect LLMs for real-time insights. Optimize queries and build intelligent systems in a hands-on live-lab environment.

This instructor-led, live training in Iowa (online or onsite) is aimed at beginner-level professionals who wish to learn how to use PostgreSQL for creating databases, writing SQL queries, manipulating data, and managing tables using both SQL commands and PGAdmin. The course also provides a basic introduction to the Timescale extension for time-series data.

By the end of this training, participants will be able to:

• Understand relational database principles and PostgreSQL architecture.
• Install, configure, and navigate PostgreSQL and PGAdmin.
• Write and run SQL queries for data selection, filtering, grouping, and joining.
• Manipulate data with SQL statements and manage database objects.
• Create and manage views and explore PostgreSQL extensions like Timescale.

This instructor-led, live training in Iowa (online or onsite) is aimed at intermediate-level developers and administrators who wish to leverage the latest features and improvements in PostgreSQL 16.

By the end of this training, participants will be able to:

• Understand the architecture and components of PostgreSQL 16.
• Utilize advanced SQL features and PostgreSQL extensions.
• Implement security best practices and access controls.
• Perform database administration tasks, including backup, recovery, and monitoring.
• Optimize database performance through tuning and indexing strategies.
• Utilize PostgreSQL's built-in tools for high availability and replication.
• Integrate PostgreSQL with modern application development frameworks.

This course provides the essential knowledge required to install, configure, and manage PostgreSQL databases effectively. Participants will learn how to handle user security, perform backups and restores, manage logs, and tune basic parameters. Through practical exercises, learners will perform real-world administration tasks and prepare for advanced topics such as performance and replication.

In this instructor-led, live training in Iowa (onsite or remote), participants will learn the general and advanced aspects of PostgreSQL, including administration, performance turning, advanced development, and replication as they step through a series of hands-on, live-lab exercises involving setup, configuration, testing, deployment and troubleshooting.

By the end of this training, participants will be able to:

• Use advanced administration techniques to configure and manage a PostgreSQL server.
• Optimize the database and queries for maximum performance.
• Replicate and scale a PostgreSQL server.

This instructor-led, live training in Iowa (online or onsite) is aimed at database admins and sysadmins who wish to use PostgreSQL to manage large-scale data while optimizing the database systems for high availability and performance.

By the end of this training, participants will be able to:

• Install and configure PostgreSQL.
• Understand the features and architecture of PostgreSQL.
• Learn how to perform database operations with SQL.
• Perform database backup and recovery to prevent data loss.
• Configure the server for high availability.
• Learn the tools and techniques for high performance tuning.
• Explore the external tools for monitoring and observability.

The course covers the fundamentals of PostgreSQL server extensions and libraries used to integrate AI techniques into database systems, including: similarity/semantic search based on embedding vectors, Text-to-SQL querying, and Retrieval-Augmented Generation (RAG). Students will learn how to install PgVector and PgAI, generate and load vector embeddings, create vector indexes, implement semantic search and RAG, develop Text-to-SQL applications using LangChain with Python/JavaScript. Demonstrations and hands-on practice reinforce the core concepts and practical skills.

The course covers the fundamentals of PostgreSQL server extensions used to integrate AI techniques into database systems, including similarity/semantic search based on embedding vectors. Students will learn how to install PgVector, generate and load vector embeddings, create vector indexes, implement semantic search. Demonstrations and hands-on practices will reinforce the core concepts and practical skills.

This hands-on course focuses on the practical aspects of performance tuning in PostgreSQL. Participants will learn to analyse query execution, optimise indexing, adjust memory and system parameters, and monitor workloads effectively. Real-world scenarios and live exercises demonstrate how to identify and resolve bottlenecks at both the database and system levels.

This course provides in-depth coverage of replication, high availability, and cluster management in PostgreSQL. Participants will build and manage multi-node environments, configure failover automation, and explore load balancing and connection pooling solutions. The course includes live replication labs and recovery simulations.

This intensive 1-day hands-on course focuses on distributed database design and implementation using the Citus extension for PostgreSQL.
Participants learn how to shard large datasets, manage distributed queries, and build scalable, fault-tolerant PostgreSQL clusters.
Real-world examples and practical labs demonstrate performance tuning, replication integration, and distributed workload management